Category: Customer Experience

What Do You Do When KYC Drives Consumers Away

Ekata

What Do You Do When KYC Drives Consumers Away?

Intersekt, 2022 Ekata Roundtable In the days of  brick-and-mortar locales, Know-Your-Customer (KYC) was a simple process; the customer was standing in front of you. You could even hold their hand as they opened an account, if you so wished. No one was frustrated by multiple captcha codes and biometric scanning requirements, abandoning the checkout process. […]

11.8.2022
Fight Identity Fraud, Provide Seamless Customer Experience

Ekata

Strike That Balance: Fight Identity Fraud, Provide Seamless Customer Experience

Intersekt Panel 2022 Asks: What Are the Trade Offs?  “The bar has been raised – and expectations are even higher,” Mastercard’s Vice President of Digital Identity, Matt Bourne When it comes to seamless, immediate customer experience, consumers have been spoiled for some time now. Streaming services, car-share rides, or pizza delivery not up to scratch? […]

11.1.2022
digital fraud prevention

Ekata

Ekata Protects 2.5 Billion Digital Interactions Globally in 2021

2021 was a transformative year for Ekata, capped by joining the Mastercard family to accelerate our shared goal of building trust in the digital economy. As consumers moved more of their lives online, online businesses grew to serve them. Over the course of the year, Ekata solutions protected billions of digital interactions from fraud and […]

2.10.2022
Assessing Data

Ekata

How Customer Outcomes Data Powers Customer Success

What is customer outcomes data? At its most simple level, a customer outcome is the result of knowing if a query to Ekata was associated with a “good” or “bad” event related to fraud that the customer might face. For example, if an ecommerce customer queries Ekata on transactional orders within their fraud decisioning workflow, […]

12.7.2021
Customer Experience Management with Probabilistic Data - Ekata

Ekata

Creating a Better Customer Experience with Probabilistic Data

Ekata offers what is called a probabilistic approach to risk with identity verification. This is different from traditional methods, which are more deterministic. The advantage to using a probabilistic solution is of scale, speed, and cost. Deterministic risk approaches are not only costly, but can result in poor customer experiences and business outcomes. So what […]

9.23.2021
How to Increase Your Thin File Customers With Account Opening API

Ekata

Increase Thin-File Customer Acquisition Rate with Account Opening API 1.1

Customers have hundreds of choices for their banking needs — and once they choose, they aren’t likely to switch. This makes capturing customers early key to achieving revenue goals. An increasing population of thin-file customers (someone with little or no credit history) is entering the market: more than 50% of digital account applicants are 35 or […]

9.20.2021
Field Data Scientist

Ekata

What are Field Data Scientists?

Ekata’s team of field data scientists (FDS) helps customers return the best possible value from our solutions. Customers meet a member of the FDS team at multiple points during the sales cycle and that relationship continues throughout their account life cycle at Ekata. So who are we? We’re a globally distributed team with people in […]

6.15.2021
Online banking and fraud prevention

Ekata

When Identity Verification Becomes a Double-Edged Sword

Original author is Kurt Weiss, Director of Enterprise Sales at Ekata   The financial system’s reliance on antiquated identity verification is a double-edged sword, cutting into both new revenue streams from the underbanked while exposing financial institutions to increased attacks from synthetic identities.  The underbanked, those without sufficient access to financial institutions, represent a key […]

3.17.2021
Balancing Customer Experience and Fraud Prevention

Ekata

Reducing False Declines, Part III: Taking Steps to Tackle Fraud

Identifying good customers in rejected transactions is half the battle, they say. Basic risk assessment rules typically place customers into two groups – good (thumbs up) and bad (thumbs down). Layering machine learning risk assessment intelligence into a fraud platform can tell you more about the good customers that you are leaving behind. But how […]

8.19.2020

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